Artificial intelligence (AI) technology is reshaping the U.S. economic structure in a data-driven manner, facilitating an adaptive transformation of the economy. This paper employs a multidimensional empirical approach, focusing on the current state and characteristics of the U.S. economic adaptive transformation, and explores the pathways through which AI optimizes resource allocation, enhances production efficiency, restructures labor markets, and reshapes regional economic landscapes. The findings provide insights for addressing challenges such as expanding fiscal deficits, rigid industrial structures, and intensifying global competition. The study reveals that AI applications in key sectors — such as healthcare, manufacturing, and finance — can significantly reduce costs and improve service efficiency for the general public. However, to mitigate labor market disruptions and regional development imbalances, policy and institutional support are essential. A tripartite framework integrating "technology-education-regulation" is proposed to ensure a balanced AI-driven economic adaptation.
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Parry Zhang (2025) studied this question.